Jorge E. Camargo

711 citations
53 papers · 506 · h-index 10

Impact in

Papers in

    • Image Retrieval and Classification Techniques 10
    • Advanced Image and Video Retrieval Techniques 10
    • Video Analysis and Summarization 9
    • Context-Aware Activity Recognition Systems 4
    • Sentiment Analysis and Opinion Mining 6
    • Advanced Text Analysis Techniques 3

Jorge E. Camargo

48 papers receiving 470 citations

Peers

Jorge E. Camargo
Comparison fields: 5 of 109
  • Computer Vision and Pattern Recognition 117
  • Health Informatics 6
  • Communication 27
  • Artificial Intelligence 112
  • Analytical Chemistry 31
Replace Thelma Domingo Palaoag with:
Thelma Domingo Palaoag Philippines
Soumi Dutta India
Zamil S. Alzamil Saudi Arabia
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Citations per field
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Citations per year

Countries citing papers authored by Jorge E. Camargo

Since Specialization
Citations

This map shows the geographic impact of Jorge E. Camargo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jorge E. Camargo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jorge E. Camargo more than expected).

Fields of papers citing papers by Jorge E. Camargo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jorge E. Camargo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jorge E. Camargo. The network helps show where Jorge E. Camargo may publish in the future.

Co-authors

The 25 scholars most cited alongside Jorge E. Camargo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jorge E. Camargo Line = papers co-authored together Jorge E. Camargo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Fine-tuning Deep Convolutional Networks for Plant Recognition.
2015156
2 201941
3 202131
4 201726
5 201826
6 201922
7 201615
8 201514
9 201213
10 200911
11 201510
12 20189
13 20129
14 20169
15 20179
16 20158
17 20206
18 20256
19 20196
20 20196

About Jorge E. Camargo

Jorge E. Camargo is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Information Systems, Software and Developmental Biology, having authored 53 papers that have together received 506 indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (10 papers), Advanced Image and Video Retrieval Techniques (10 papers), Video Analysis and Summarization (9 papers), Sentiment Analysis and Opinion Mining (6 papers), Context-Aware Activity Recognition Systems (4 papers), Mobile Health and mHealth Applications (4 papers), Software Engineering Research (4 papers) and Advanced Text Analysis Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (117 citations), Health Informatics (6 citations), Communication (27 citations), Artificial Intelligence (112 citations) and Analytical Chemistry (31 citations). Jorge E. Camargo has collaborated with scholars based in Colombia, United Kingdom and Italy. Frequent co-authors include Fabio A. González, Juan C. Correa, Alvaro David Orjuela-Cañón, Juan Carlos Caicedo, Felipe Restrepo‐Calle, Jairo Aponte, Julien Wist, Francisco J. Ávila Gómez, Luc Patiny and Pierre Esseiva. Their work appears in journals such as Journal of Information Science, Frontiers in Public Health, Information Technology & Tourism, Forensic Science International and Cities.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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